class_docstr: Class for the positive reals metric.
  
  It is a particular case in dimension 1
  of the SPD affine-invariant metric
  with a power affine coefficient equal to one.
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docstr: Compute the positive reals squared distance.
  
  Compute the Riemannian squared distance between point_a and point_b.
  
  Parameters
  ----------
  point_a : array-like, shape=[..., 1]
      Point.
  point_b : array-like, shape=[..., 1]
      Point.
  
  Returns
  -------
  squared_dist : array-like, shape=[...]
      Riemannian squared distance.
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code: def squared_dist(self, point_a, point_b):
      """Compute the positive reals squared distance.
  
      Compute the Riemannian squared distance between point_a and point_b.
  
      Parameters
      ----------
      point_a : array-like, shape=[..., 1]
          Point.
      point_b : array-like, shape=[..., 1]
          Point.
  
      Returns
      -------
      squared_dist : array-like, shape=[...]
          Riemannian squared distance.
      """
      ratio = gs.squeeze(point_b / point_a, axis=-1)
      return (gs.log(ratio)) ** 2
  
file_path: geomstats/geomstats/geometry/positive_reals.py
imports: import geomstats.backend
  from geomstats.geometry.base import VectorSpaceOpenSet
  from geomstats.geometry.euclidean import Euclidean
  from geomstats.geometry.riemannian_metric import RiemannianMetric
label_desc: Use image node_id 4 for calling the PositiveRealsMetric obj's underlying member method code with example usage: obj.squared_dist(point_a, point_b) and returns: unknown